Already one year that the MEOP portal has been launched!
A very successful year for our growing community… in one year, 23 new publications using MEOP data have been added, increasing the number of MEOP-related peer-reviewed publications to 94. Simultaneously, the MEOP-CTD database has been included in major oceanographic data centres, including the NODC, Coriolis, and the BODC. More than 100 individual users have requested the database using the MEOP web interface.
It is now time to release a major update of the MEOP-CTD database. In this new version, namely the MEOP-CTD_2016-07-12, more animal-borne instrument data are included. The number of profile publicly distributed has increased from slightly less than 300,000 to almost 400,000 profiles. Also, 125,000 other profiles are included into the database, although they remain private, i.e. accessible only upon request. In total, the database has now reached the 500,000 profiles milestone.
Two datasets have been added in particular, that expand considerably the spatial coverage of the MEOP-CTD database. The first consists of 30,000+ profiles in the northeastern sector of the North Pacific, obtained by instrumenting Northern Elephant Seals in California (D. Costa, University of Santa Cruz, USA group). The second dataset provides 70,000+ temperature-only profiles in the Labrador Sea/Irminger Sea and in Baffin Bay/Hudson Bay/Gulf of St Lawrence shelf areas (see e.g. Straneo et al. 2010, Grist et al. 2011, 2014) from Hooded and Ringed seals (G. Stenson, DFO, Canada group).
Finally, a new stream of data has been added, obtained from TDR (time-depth recorder) attached to elephant seals in the Kerguelen area (PI: C. Guinet, CEBC, French group). The MEOP-TDR database includes 285,000 temperature profiles obtained from 69 different loggers. This dataset has a very high spatial and temporal resolution, with 60-100 profiles per day (i.e. ~4 profiles/hour), allowing to observe mesoscale ocean activity.
To facilitate the access to our database, we have developed Matlab tools and Python tools to read and manipulate files with the netCDF format. Note also that this format can be easily read by the software Ocean Data View. For those not comfortable with the netCDF format, a csv format is also available.
Please continue using our data, and support us by providing us your feedbacks, citing our work and spreading the word around you.